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ORCIDFrancisco J. R. Ruiz
Person information
- affiliation: DeepMind
- affiliation: Columbia University, Department of Computer Science, NY, USA
- affiliation: University of Cambridge, Department of Engineering, UK
- affiliation: Charles III University of Madrid, Department of Signal Processing and Communications, Madrid, Spain
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2020 – today
- 2024
[j9]Bernardino Romera-Paredes
, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M. Pawan Kumar, Emilien Dupont, Francisco J. R. Ruiz, Jordan S. Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, Alhussein Fawzi:
Mathematical discoveries from program search with large language models. Nat. 625(7995): 468-475 (2024)- [i18]Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli:
Quantum Circuit Optimization with AlphaTensor. CoRR abs/2402.14396 (2024) - 2023
- [j8]Xu Han, Xiaohui Chen, Francisco J. R. Ruiz, Li-Ping Liu:
Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation. J. Mach. Learn. Res. 24: 97:1-97:30 (2023) - [e7]Francisco J. R. Ruiz, Jennifer G. Dy, Jan-Willem van de Meent:
International Conference on Artificial Intelligence and Statistics, 25-27 April 2023, Palau de Congressos, Valencia, Spain. Proceedings of Machine Learning Research 206, PMLR 2023 [contents] - 2022
- [j7]Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis, Pushmeet Kohli:
Discovering faster matrix multiplication algorithms with reinforcement learning. Nat. 610(7930): 47-53 (2022) - [e6]Gustau Camps-Valls, Francisco J. R. Ruiz, Isabel Valera:
International Conference on Artificial Intelligence and Statistics, AISTATS 2022, 28-30 March 2022, Virtual Event. Proceedings of Machine Learning Research 151, PMLR 2022 [contents] - [e5]Javier Antorán, Arno Blaas, Fan Feng, Sahra Ghalebikesabi, Ian Mason, Melanie F. Pradier, David Rohde, Francisco J. R. Ruiz, Aaron Schein:
Proceedings on "I Can't Believe It's Not Better! - Understanding Deep Learning Through Empirical Falsification" at NeurIPS 2022 Workshops, 03 December 2022, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 187, PMLR 2022 [contents] - 2021
- [c19]Xiaohui Chen, Xu Han, Jiajing Hu, Francisco J. R. Ruiz, Li-Ping Liu:
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation. ICML 2021: 1630-1639 - [c18]Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet:
Unbiased gradient estimation for variational auto-encoders using coupled Markov chains. UAI 2021: 707-717 - [c17]Michalis K. Titsias, Francisco J. R. Ruiz, Sotirios Nikoloutsopoulos, Alexandre Galashov:
Information theoretic meta learning with Gaussian processes. UAI 2021: 1597-1606 - [e4]Melanie F. Pradier, Aaron Schein, Stephanie L. Hyland, Francisco J. R. Ruiz, Jessica Zosa Forde:
I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, Virtual Workshop, December 13, 2021. Proceedings of Machine Learning Research 163, PMLR 2021 [contents] - [i17]Xiaohui Chen, Xu Han, Jiajing Hu, Francisco J. R. Ruiz, Li-Ping Liu:
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation. CoRR abs/2106.06189 (2021) - 2020
- [j6]Adji Bousso Dieng, Francisco J. R. Ruiz, David M. Blei:
Topic Modeling in Embedding Spaces. Trans. Assoc. Comput. Linguistics 8: 439-453 (2020) - [c16]Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz:
VarGrad: A Low-Variance Gradient Estimator for Variational Inference. NeurIPS 2020 - [e3]Cheng Zhang, Francisco J. R. Ruiz, Thang D. Bui, Adji Bousso Dieng, Dawen Liang:
Symposium on Advances in Approximate Bayesian Inference, AABI 2019, Vancouver, BC, Canada, December 8, 2019. Proceedings of Machine Learning Research 118, PMLR 2020 [contents] - [e2]Jessica Zosa Forde, Francisco J. R. Ruiz, Melanie F. Pradier, Aaron Schein:
"I Can't Believe It's Not Better!" at NeurIPS Workshops, Virtual, December 12, 2020. Proceedings of Machine Learning Research 137, PMLR 2020 [contents] - [i16]Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet:
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains. CoRR abs/2010.01845 (2020) - [i15]Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz:
VarGrad: A Low-Variance Gradient Estimator for Variational Inference. CoRR abs/2010.10436 (2020)
2010 – 2019
- 2019
- [c15]Michalis K. Titsias, Francisco J. R. Ruiz:
Unbiased Implicit Variational Inference. AISTATS 2019: 167-176 - [c14]Francisco J. R. Ruiz, Michalis K. Titsias:
A Contrastive Divergence for Combining Variational Inference and MCMC. ICML 2019: 5537-5545 - [e1]Francisco J. R. Ruiz, Cheng Zhang, Dawen Liang, Thang D. Bui:
Symposium on Advances in Approximate Bayesian Inference, AABI 2018, Montréal, QC, Canada, December 2, 2018. Proceedings of Machine Learning Research 96, PMLR 2019 [contents] - [i14]Francisco J. R. Ruiz, Michalis K. Titsias:
A Contrastive Divergence for Combining Variational Inference and MCMC. CoRR abs/1905.04062 (2019) - [i13]Robert Donnelly, Francisco J. R. Ruiz, David M. Blei, Susan Athey:
Counterfactual Inference for Consumer Choice Across Many Product Categories. CoRR abs/1906.02635 (2019) - [i12]Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei:
Topic Modeling in Embedding Spaces. CoRR abs/1907.04907 (2019) - [i11]Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei:
The Dynamic Embedded Topic Model. CoRR abs/1907.05545 (2019) - [i10]Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei, Michalis K. Titsias:
Prescribed Generative Adversarial Networks. CoRR abs/1910.04302 (2019) - 2018
- [j5]Francisco J. R. Ruiz, Isabel Valera, Lennart Svensson, Fernando Pérez-Cruz:
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation. IEEE Trans. Cogn. Commun. Netw. 4(2): 177-191 (2018) - [c13]Francisco J. R. Ruiz, Michalis K. Titsias, Adji B. Dieng, David M. Blei:
Augment and Reduce: Stochastic Inference for Large Categorical Distributions. ICML 2018: 4400-4409 - [i9]Susan Athey, David M. Blei, Robert Donnelly, Francisco J. R. Ruiz, Tobias Schmidt:
Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data. CoRR abs/1801.07826 (2018) - [i8]Francisco J. R. Ruiz, Michalis K. Titsias, Adji B. Dieng, David M. Blei:
Augment and Reduce: Stochastic Inference for Large Categorical Distributions. CoRR abs/1802.04220 (2018) - [i7]Michalis K. Titsias, Francisco J. R. Ruiz:
Unbiased Implicit Variational Inference. CoRR abs/1808.02078 (2018) - [i6]Francisco J. R. Ruiz, Isabel Valera, Lennart Svensson, Fernando Pérez-Cruz:
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation. CoRR abs/1810.09261 (2018) - [i5]Maryam Fatemi, Karl Granström, Lennart Svensson, Francisco J. R. Ruiz, Lars Hammarstrand:
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling. CoRR abs/1811.03154 (2018) - 2017
- [j4]Maryam Fatemi, Karl Granström, Lennart Svensson, Francisco J. R. Ruiz, Lars Hammarstrand:
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling. IEEE Trans. Signal Process. 65(11): 2814-2827 (2017) - [c12]Christian A. Naesseth, Francisco J. R. Ruiz, Scott W. Linderman, David M. Blei:
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms. AISTATS 2017: 489-498 - [c11]Maja Rudolph, Francisco J. R. Ruiz, Susan Athey, David M. Blei:
Structured Embedding Models for Grouped Data. NIPS 2017: 251-261 - [c10]Li-Ping Liu, Francisco J. R. Ruiz, Susan Athey, David M. Blei:
Context Selection for Embedding Models. NIPS 2017: 4816-4825 - [i4]Maja Rudolph, Francisco J. R. Ruiz, Susan Athey, David M. Blei:
Structured Embedding Models for Grouped Data. CoRR abs/1709.10367 (2017) - [i3]Francisco J. R. Ruiz, Susan Athey, David M. Blei:
SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements. CoRR abs/1711.03560 (2017) - 2016
- [j3]Isabel Valera, Francisco J. R. Ruiz, Pablo M. Olmos, Carlos Blanco, Fernando Pérez-Cruz:
Infinite Continuous Feature Model for Psychiatric Comorbidity Analysis. Neural Comput. 28(2): 354-381 (2016) - [j2]Isabel Valera, Francisco J. R. Ruiz, Fernando Pérez-Cruz:
Infinite Factorial Unbounded-State Hidden Markov Model. IEEE Trans. Pattern Anal. Mach. Intell. 38(9): 1816-1828 (2016) - [c9]Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei:
The Generalized Reparameterization Gradient. NIPS 2016: 460-468 - [c8]Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei:
Exponential Family Embeddings. NIPS 2016: 478-486 - [c7]Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei:
Overdispersed Black-Box Variational Inference. UAI 2016 - [i2]Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei:
Exponential Family Embeddings. CoRR abs/1608.00778 (2016) - 2015
- [c6]Isabel Valera, Francisco J. R. Ruiz, Lennart Svensson, Fernando Pérez-Cruz:
A Bayesian nonparametric approach for blind multiuser channel estimation. EUSIPCO 2015: 2766-2770 - [c5]Isabel Valera, Francisco J. R. Ruiz, Lennart Svensson, Fernando Pérez-Cruz:
Infinite Factorial Dynamical Model. NIPS 2015: 1666-1674 - 2014
- [j1]Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz:
Bayesian nonparametric comorbidity analysis of psychiatric disorders. J. Mach. Learn. Res. 15(1): 1215-1247 (2014) - [c4]Prem Gopalan, Francisco J. R. Ruiz, Rajesh Ranganath, David M. Blei:
Bayesian Nonparametric Poisson Factorization for Recommendation Systems. AISTATS 2014: 275-283 - [c3]Isabel Valera, Francisco J. R. Ruiz, Fernando Pérez-Cruz:
Sinfinite factorial unbounded hidden Markov model for blind multiuser channel estimation. CIP 2014: 1-6 - [i1]Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz:
Bayesian nonparametric comorbidity analysis of psychiatric disorders. CoRR abs/1401.7620 (2014) - 2012
- [c2]Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz:
Bayesian Nonparametric Modeling of Suicide Attempts. NIPS 2012: 1862-1870 - 2011
- [c1]Francisco J. R. Ruiz, Fernando Pérez-Cruz:
Zero-error codes for the noisy-typewriter channel. ITW 2011: 495-497
Coauthor Index
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last updated on 2024-04-25 01:17 CEST by the dblp team
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